Rossant IPython Interactive Computing and Visualization Cookbook

Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes
1. Auflage 2024
ISBN: 978-1-78328-482-5
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 512 Seiten

Key FeaturesBook DescriptionIntended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists. Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.What you will learn - Code better by writing highquality, readable, and welltested programs; profiling and optimizing your code, and conducting reproducible interactive computing experiments
- Master all of the new features of the IPython notebook, including the interactive HTML/JavaScript widgets
- Analyze data with Bayesian and frequentist statistics (Pandas, PyMC, and R), and learn from data with machine learning (scikitlearn)
- Gain valuable insights into signals, images, and sounds with SciPy, scikitimage, and OpenCV
- Learn how to write blazingly fast Python programs with NumPy, PyTables, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA and OpenCL), parallel IPython, MPI, and many more
Who this book is for

Autoren/Hrsg.

Rossant, Cyrille

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung

Inhaltsverzeichnis

Table of Contents - Basic Interactive Computing with Ipython
- Best practices in Interactive Computing
- Master the Notebook
- Profiling and Optimization
- High-Performance Computing
- Advanced Visualization
- Statistical Data Analysis
- Machine Learning
- Numerical Optimization
- Signal Processing
- Image and Audio Processing
- Deterministic Dynamical Systems
- Stochastic Dynamical Systems
- Graphs and Geometry
- Symbolic and Numerical Mathematics

Über Autor(innen)

Rossant Cyrille :

Cyrille Rossant, PhD, is a neuroscience researcher and software engineer at University College London. He is a graduate of École Normale Supérieure, Paris, where he studied mathematics and computer science. He has also worked at Princeton University and Collège de France. While working on data science and software engineering projects, he gained experience in numerical computing, parallel computing, and high-performance data visualization. He is the author of Learning IPython for Interactive Computing and Data Visualization, Second Edition, Packt Publishing.